Optimization of the wetting-drying characteristics of hydrophobic metal organic frameworks via crystallite size: The role of hydrogen bonding between intruded and bulk liquid

Hypothesis: The behavior of Heterogeneous Lyophobic Systems (HLSs) comprised of a lyophobic porous material and a corresponding non-wetting liquid is affected by a variety of different structural parameters of the porous material. Dependence on exogenic properties such as crystallite size is desirable for system tuning as they are much more facilely modified. We explore the dependence of intrusion pressure and intruded volume on crystallite size, testing the hypothesis that the connection between internal cavities and bulk water facilitates intrusion via hydrogen bonding, a phenomenon that is magnified in smaller crystallites with a larger surface/volume ratio. Experiments: Water intrusion/extrusion pressures and intrusion volume were experimentally measured for ZIF-8 samples of various crystallite sizes and compared to previously reported values. Alongside the practical research, molecular dynamics simulations and stochastic modeling were performed to illustrate the effect of crystallite size on the properties of the HLSs and uncover the important role of hydrogen bonding within this phenomenon. Findings: A reduction in crystallite size led to a significant decrease of intrusion and extrusion pressures below 100 nm. Simulations indicate that this behavior is due to a greater number of cages being in proximity to bulk water for smaller crystallites, allowing cross-cage hydrogen bonds to stabilize the intruded state and lower the threshold pressure of intrusion and extrusion. This is accompanied by a reduction in the overall intruded volume. Simulations demonstrate that this phenomenon is linked to ZIF-8 surface half-cages exposed to water being occupied by water due to non-trivial termination of the crystallites, even at atmospheric pressure

Effect of Systemic Hypertension With Versus Without Left Ventricular Hypertrophy on the Progression of Atrial Fibrillation (from the Euro Heart Survey).

Hypertension is a risk factor for both progression of atrial fibrillation (AF) and development of AF-related complications, that is major adverse cardiac and cerebrovascular events (MACCE). It is unknown whether left ventricular hypertrophy (LVH) as a consequence of hypertension is also a risk factor for both these end points. We aimed to assess this in low-risk AF patients, also assessing gender-related differences. We included 799 patients from the Euro Heart Survey with nonvalvular AF and a baseline echocardiogram. Patients with and without hypertension were included. End points after 1 year were occurrence of AF progression, that is paroxysmal AF becoming persistent and/or permanent AF, and MACCE. Echocardiographic LVH was present in 33% of 379 hypertensive patients. AF progression after 1 year occurred in 10.2% of 373 patients with rhythm follow-up. In hypertensive patients with LVH, AF progression occurred more frequently as compared with hypertensive patients without LVH (23.3% vs 8.8%, p = 0.011). In hypertensive AF patients, LVH was the most important multivariably adjusted determinant of AF progression on multivariable logistic regression (odds ratio 4.84, 95% confidence interval 1.70 to 13.78, p = 0.003). This effect was only seen in male patients (27.5% vs 5.8%, p = 0.002), while in female hypertensive patients, no differences were found in AF progression rates regarding the presence or absence of LVH (15.2% vs 15.0%, p = 0.999). No differences were seen in MACCE for hypertensive patients with and without LVH. In conclusion, in men with hypertension, LVH is associated with AF progression. This association seems to be absent in hypertensive women

The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males

The polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways. Abbreviations: AP: autophagosome; AUC: area under the curve; BafA1: bafilomycin A1; COVID-19: coronavirus disease-2019; HCQ: hydroxychloroquine; RAP: rapamycin; ROC: receiver operating characteristic; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; TLR: toll like receptor; TNF/TNF-α: tumor necrosis factor

An explainable model of host genetic interactions linked to COVID-19 severity

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as "Respiratory or thoracic disease", supporting their link with COVID-19 severity outcome.A multifaceted computational strategy identifies 16 genetic variants contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing dataset of a cohort of Italian patients

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

Updated measurement of decay-time-dependent CP asymmetries in D-0 -> K+ K- and D-0 -> pi(+)pi(-) decays

A search for decay-time-dependent charge-parity (CP) asymmetry in D0 \u2192 K+ K 12 and D0 \u2192 \u3c0+ \u3c0 12 decays is performed at the LHCb experiment using proton-proton collision data recorded at a center-of-mass energy of 13 TeV, and corresponding to an integrated luminosity of 5.4 fb^ 121. The D0 mesons are required to originate from semileptonic decays of b hadrons, such that the charge of the muon identifies the flavor of the neutral D meson at production. The asymmetries in the effective decay widths of D0 and anti-D0 mesons are determined to be A_\u393(K+ K 12) = ( 124.3 \ub1 3.6 \ub1 0.5) 7 10^ 124 and A_\u393(\u3c0+ \u3c0 12) = (2.2 \ub1 7.0 \ub1 0.8) 7 10^ 124 , where the uncertainties are statistical and systematic, respectively. The results are consistent with CP symmetry and, when combined with previous LHCb results, yield A_\u393(K+ K 12) = ( 124.4 \ub1 2.3 \ub1 0.6) 7 10^ 124 and A_\u393(\u3c0+ \u3c0 12) = (2.5 \ub1 4.3 \ub1 0.7) 7 10^ 124

Updated measurement of decay-time-dependent CP asymmetries in D-0 -> K+ K- and D-0 -> pi(+)pi(-) decays

A search for decay-time-dependent charge-parity (CP) asymmetry in D-0 -> K+ K- and D-0 -> pi(+)pi(-) eff decays is performed at the LHCb experiment using proton-proton collision data recorded at a center-of-mass energy of 13 TeV, and corresponding to an integrated luminosity of 5.4 fb(-1). The D-0 mesons are required to originate from semileptonic decays of b hadrons, such that the charge of the muon identifies the flavor of the neutral D meson at production. The asymmetries in the effective decay widths of D-0 and (D) over bar (0) mesons are determined to be A(Gamma)(K+ K-) = (-4.3 +/- 3.6 +/- 0.5) x 10(-4) and A(Gamma) (K+ K- ) = (2.2 +/- 7.0 +/- 0.8) x 10(-4), where the uncertainties are statistical and systematic, respectively. The results are consistent with CP symmetry and, when combined with previous LHCb results, yield A(Gamma) (K+ K-) = (-4.4 +/- 2.3 +/- 0.6) x 10(-4) and A(Gamma) (pi(+)pi(-))= (2.5 +/- 4.3 +/- 0.7) x 10(-4)